Customers are often time-sensitive and typically desire to wait a minimal amount of time for consumer items requiring preparation, such as food, floral arrangements, pharmaceuticals and other items, while expecting no sacrifice to the quality of their items. Additionally, businesses, such as restaurants, generally benefit from decreased customer wait time, and increased table turns. Therefore, reduced wait time is beneficial to the customers, because they are generally more satisfied and likely to return due to the relatively small amount of time they have to wait for their items. Reduced wait time is also beneficial to the restaurant owner, allowing higher volumes of customers that can be serviced. However, reduced wait time is often difficult to achieve, particularly with respect to items that require a relatively long period of time to prepare.
One such example is a deep dish pizza, which often can take as long as forty minutes or more to prepare and cook. With respect to a restaurant having a menu including a variety of deep dish pizzas, for example, customers will often have to wait a relatively long period of time to receive their meals after ordering.
What is needed is a predictive ordering system configured to reduce customer wait time by utilizing logic to preorder consumer items based at least in part on aggregate historical purchase information as well as display information regarding these in-progress items to potential customers for claiming and eventual purchase.